Site-specific weed management (SSWM) can provide significant herbicide savings but requires the reliable detection of weed populations. In this work, the effect of sample size on sampling precision was studied in four sub-field areas of winter cereals infested with Galium aparine. Plots of 1170 m², 4212 m², 2592 m² and 2880 m² were marked and the positions of all G. aparine individuals were recorded using a precise navigation system. Mapping cells of 3 m × 3 m were arranged over experimental data and then various sampling intensities of G. aparine populations were simulated. The relative root mean square error, mean absolute percentage error (MAPE), and false negative rate were calculated and plotted against individual sampling intensities. Regressions were fitted to non-linear models. Experimental plots had relatively low mean densities of G. aparine (1.00–2.98 plants m⁻²) and the spatial distributions of plants were patchy in all cases. The values of all error measures decreased with increasing sampling intensity. On the basis of the fitted model, keeping MAPE below 30% required the sampling of 32.2% of the total area for the low-density population and 13.4% for the highest-density population. The results presented demonstrate that reliable sampling of low-density populations requires a very high sampling intensity and could be helpful in the design of reliable sampling strategies for SSWM.

特定地点的杂草管理 (SSWM) 可以显着节省除草剂，但需要可靠地检测杂草种群。在这项工作中，研究了样本量对样本精度的影响，在四个受肝素镓侵染的冬季谷物亚田区中进行了研究。标记了 1170 m ²、4212 m ²、2592 m ²和 2880 m ^{2 的}地块，并使用精确导航系统记录了所有G. aparine个体的位置。将 3 m × 3 m 的作图单元排列在实验数据上，然后对G. aparine进行各种采样强度人群进行了模拟。计算相对均方根误差、平均绝对百分比误差 (MAPE) 和假阴性率，并根据个体采样强度绘制图表。回归拟合非线性模型。实验地块的G. aparine平均密度相对较低（1.00-2.98 株 m ^-2) 并且在所有情况下植物的空间分布都是不完整的。所有误差测量值随着采样强度的增加而降低。在拟合模型的基础上，保持 MAPE 低于 30% 需要抽样占总面积的 32.2% 的低密度人口和 13.4% 的最高密度人口。所呈现的结果表明，低密度种群的可靠采样需要非常高的采样强度，并且可能有助于设计 SSWM 的可靠采样策略。